[UPDATE] Google's DeepMind AI Makes A Major Breakthrough

Published June 9th at 11:30am

Update 2

Having beaten Lee Se-dol, a player considered to be one of the best Go players of all time, Google's AI will now take on Ke Jie - is the reigning top-ranked Go player in the world. He’s agreed to play the AI program at the ancient board game, although a date and location are yet to be set. According to Ars Technica, Ke said on his Weibo account in March: “Even if AlphaGo can defeat Lee Se-dol, it can’t beat me.”

Although it suffered its first defeat in the Google DeepMind Challenge Match last Sunday, the Go-playing AI AlphaGo has beaten world-class player Lee Se-dol for a fourth time to win the five-game series 4-1 overall. The final game turned out to be very close, with both sides fighting hard and going deep into overtime.

According to The Verge, The win came after a "bad mistake" made early in the game, according to DeepMind founder Demis Hassabis, leaving AlphaGo "trying hard to claw it back." By winning the final game despite its blip in the fourth, AlphaGo has demonstrated beyond doubt its superiority over one of the world's best Go players, reaffirming a major milestone for artificial intelligence in the process...................................................

In 1996, IBM’s chess playing computer Deep Blue defeated the then world champion Garry Kasparov. This was a pivotal event in the field of artificial intelligence because at that moment, a machine surpassed a human intellect for the first time in history. Since then, machine learning and artificial intelligence has progressed at an impressive rate and recently another breakthrough was announced; Google’s DeepMind programme ‘AlphaGo’ has beaten a top human player at the game of Go, the ancient Eastern game of strategy and intuition that has evaded AI experts for decades.

Intelligent machines have beaten humans at most games held up as measures of human intellect, but with Go - a centuries old game that is significantly more complex than chess - humans have maintained an edge over even the most advanced and agile computers - in fact, there are (apparently) sexquinquagintillion possible moves. As Google put it themselves in a blog post, which makes the game incredibly complex. Mapping out every possible move simply won't work for Go, making it the one game computers can't beat humans at - until now of course...

It was the principles of machine learning that made this feat from DeepMind possible. Unlike previous computer game programs like Deep Blue, DeepMind doesn't use any special game-specific programming, instead relying on what is known as ‘general AI’. Previously, Google applied it to the classic game ‘Breakout’ when a machine was given a general-purpose AI algorithm and subsequently learnt how to play the game. AlphaGo uses these same principles when tackling the game of Go.

The researchers at DeepMind says that, because its approach is general purpose; "our hope is that one day they could be extended to help us address some of society’s toughest and most pressing problems, from climate modelling to complex disease analysis”. We’re a long way away from this just yet, but Google has just taken a major step in the right direction.